Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.14287 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909041670750208 |
|---|---|
| author | Zhang, Jiahui Zhu, Yifei Feng, Chuqiao Ma, Yingjin Xu, Chao Lan, Zhenggang |
| author_facet | Zhang, Jiahui Zhu, Yifei Feng, Chuqiao Ma, Yingjin Xu, Chao Lan, Zhenggang |
| contents | Conical intersections play central roles in photoinduced reactions. However, comprehensive conical-intersection datasets that could advance our understanding of excited-state reaction processes remain scarce. To address this gap, we constructed a quantum chemistry dataset containing ground-state and conical-intersection structures of small molecules (up to ten heavy atoms: C, N, O, F). Ground-state geometries were optimized at the semi-empirical OM2 level, with single-point energies calculated at the OM2/MRCI level. Conical-intersection geometries and energies were also computed at the OM2/MRCI level. This dataset is designed to enable a deep integration of photochemistry with machine learning, bridging the gap between photochemical insight and data-driven approaches. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_14287 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A quantum chemistry dataset containing ground-state and conical-intersection structures of 260k molecules Zhang, Jiahui Zhu, Yifei Feng, Chuqiao Ma, Yingjin Xu, Chao Lan, Zhenggang Chemical Physics Conical intersections play central roles in photoinduced reactions. However, comprehensive conical-intersection datasets that could advance our understanding of excited-state reaction processes remain scarce. To address this gap, we constructed a quantum chemistry dataset containing ground-state and conical-intersection structures of small molecules (up to ten heavy atoms: C, N, O, F). Ground-state geometries were optimized at the semi-empirical OM2 level, with single-point energies calculated at the OM2/MRCI level. Conical-intersection geometries and energies were also computed at the OM2/MRCI level. This dataset is designed to enable a deep integration of photochemistry with machine learning, bridging the gap between photochemical insight and data-driven approaches. |
| title | A quantum chemistry dataset containing ground-state and conical-intersection structures of 260k molecules |
| topic | Chemical Physics |
| url | https://arxiv.org/abs/2605.14287 |